Comprehensive analysis of prognostic immune-related genes and drug sensitivity in cervical cancer

Abstract Background Cervical cancer (CC) is the leading cause of cancer-related death in women. A limited number of studies have investigated whether immune-prognostic features can be used to predict the prognosis of CC. This study aimed to develop an improved prognostic risk scoring model (PRSM) fo...

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Autores principales:	Ya-Nan Pi, Jun-Nan Guo, Ge Lou, Bin-Bin Cui
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	Cervical cancer (CC) Immune-related genes (IRGs) Prognosis Prognostic risk score model (PRSM) Drug sensitivity Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Cytology QH573-671
Acceso en línea:	https://doaj.org/article/508595587ff942bb99c18f05fe89ee2e
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spelling	oai:doaj.org-article:508595587ff942bb99c18f05fe89ee2e2021-12-05T12:23:42ZComprehensive analysis of prognostic immune-related genes and drug sensitivity in cervical cancer10.1186/s12935-021-02333-91475-2867https://doaj.org/article/508595587ff942bb99c18f05fe89ee2e2021-12-01T00:00:00Zhttps://doi.org/10.1186/s12935-021-02333-9https://doaj.org/toc/1475-2867Abstract Background Cervical cancer (CC) is the leading cause of cancer-related death in women. A limited number of studies have investigated whether immune-prognostic features can be used to predict the prognosis of CC. This study aimed to develop an improved prognostic risk scoring model (PRSM) for CC based on immune-related genes (IRGs) to predict survival and determine the key prognostic IRGs. Methods We downloaded the gene expression profiles and clinical data of CC patients from the TCGA and GEO databases. The ESTIMATE algorithm was used to calculate the score for both immune and stromal cells. Differentially expressed genes (DEGs) in different subpopulations were analyzed by “Limma”. A weighted gene co-expression network analysis (WGCNA) was used to establish a DEG co-expression module related to the immune score. Immune-related gene pairs (IRGPs) were constructed, and univariate- and Lasso-Cox regression analyses were used to analyze prognosis and establish a PRSM. A log-rank test was used to verify the accuracy and consistency of the scoring model. Identification of the predicted key IRG was ensured by the application of functional enrichment, DisNor, protein–protein interactions (PPIs) and heatmap. Finally, we extracted the key prognostic immune-related genes from the gene expression data, validated the key genes by immunohistochemistry and analyzed the correlation between their expression and drug sensitivity. Results A new PRSM was developed based on 22 IRGPs. The prognosis of the low-risk group in the model group (P < 0.001) and validation group (P = 0.039) was significantly better than that in the high-risk group. Furthermore, M1 and M2 macrophages were highly expressed in the low-risk group. Retinoic acid-inducible gene-I (RIG-I)-like receptors (RLRs) and the Janus kinase-signal transducer and activator of transcription (JAK-STAT) signaling pathway were significantly enriched in the low-risk group. Three representative genes (CD80, CD28, and LCP2) were markers of CC prognosis. CD80 and CD28 may more prominent represent important indicators to improve patient prognosis. These key genes was positively correlated with drug sensitivity. Finally, we found that differences in the sensitivity to JNK inhibitors could be distinguished based on the use and risk grouping of this PRSM. Conclusions The prognostic model based on the IRGs and key genes have potential clinical significance for predicting the prognosis of CC patients, providing a foundation for clinical prognosis judgment and individualized treatment.Ya-Nan PiJun-Nan GuoGe LouBin-Bin CuiBMCarticleCervical cancer (CC)Immune-related genes (IRGs)PrognosisPrognostic risk score model (PRSM)Drug sensitivityNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282CytologyQH573-671ENCancer Cell International, Vol 21, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Cervical cancer (CC) Immune-related genes (IRGs) Prognosis Prognostic risk score model (PRSM) Drug sensitivity Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Cytology QH573-671
spellingShingle	Cervical cancer (CC) Immune-related genes (IRGs) Prognosis Prognostic risk score model (PRSM) Drug sensitivity Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Cytology QH573-671 Ya-Nan Pi Jun-Nan Guo Ge Lou Bin-Bin Cui Comprehensive analysis of prognostic immune-related genes and drug sensitivity in cervical cancer
description	Abstract Background Cervical cancer (CC) is the leading cause of cancer-related death in women. A limited number of studies have investigated whether immune-prognostic features can be used to predict the prognosis of CC. This study aimed to develop an improved prognostic risk scoring model (PRSM) for CC based on immune-related genes (IRGs) to predict survival and determine the key prognostic IRGs. Methods We downloaded the gene expression profiles and clinical data of CC patients from the TCGA and GEO databases. The ESTIMATE algorithm was used to calculate the score for both immune and stromal cells. Differentially expressed genes (DEGs) in different subpopulations were analyzed by “Limma”. A weighted gene co-expression network analysis (WGCNA) was used to establish a DEG co-expression module related to the immune score. Immune-related gene pairs (IRGPs) were constructed, and univariate- and Lasso-Cox regression analyses were used to analyze prognosis and establish a PRSM. A log-rank test was used to verify the accuracy and consistency of the scoring model. Identification of the predicted key IRG was ensured by the application of functional enrichment, DisNor, protein–protein interactions (PPIs) and heatmap. Finally, we extracted the key prognostic immune-related genes from the gene expression data, validated the key genes by immunohistochemistry and analyzed the correlation between their expression and drug sensitivity. Results A new PRSM was developed based on 22 IRGPs. The prognosis of the low-risk group in the model group (P < 0.001) and validation group (P = 0.039) was significantly better than that in the high-risk group. Furthermore, M1 and M2 macrophages were highly expressed in the low-risk group. Retinoic acid-inducible gene-I (RIG-I)-like receptors (RLRs) and the Janus kinase-signal transducer and activator of transcription (JAK-STAT) signaling pathway were significantly enriched in the low-risk group. Three representative genes (CD80, CD28, and LCP2) were markers of CC prognosis. CD80 and CD28 may more prominent represent important indicators to improve patient prognosis. These key genes was positively correlated with drug sensitivity. Finally, we found that differences in the sensitivity to JNK inhibitors could be distinguished based on the use and risk grouping of this PRSM. Conclusions The prognostic model based on the IRGs and key genes have potential clinical significance for predicting the prognosis of CC patients, providing a foundation for clinical prognosis judgment and individualized treatment.
format	article
author	Ya-Nan Pi Jun-Nan Guo Ge Lou Bin-Bin Cui
author_facet	Ya-Nan Pi Jun-Nan Guo Ge Lou Bin-Bin Cui
author_sort	Ya-Nan Pi
title	Comprehensive analysis of prognostic immune-related genes and drug sensitivity in cervical cancer
title_short	Comprehensive analysis of prognostic immune-related genes and drug sensitivity in cervical cancer
title_full	Comprehensive analysis of prognostic immune-related genes and drug sensitivity in cervical cancer
title_fullStr	Comprehensive analysis of prognostic immune-related genes and drug sensitivity in cervical cancer
title_full_unstemmed	Comprehensive analysis of prognostic immune-related genes and drug sensitivity in cervical cancer
title_sort	comprehensive analysis of prognostic immune-related genes and drug sensitivity in cervical cancer
publisher	BMC
publishDate	2021
url	https://doaj.org/article/508595587ff942bb99c18f05fe89ee2e
work_keys_str_mv	AT yananpi comprehensiveanalysisofprognosticimmunerelatedgenesanddrugsensitivityincervicalcancer AT junnanguo comprehensiveanalysisofprognosticimmunerelatedgenesanddrugsensitivityincervicalcancer AT gelou comprehensiveanalysisofprognosticimmunerelatedgenesanddrugsensitivityincervicalcancer AT binbincui comprehensiveanalysisofprognosticimmunerelatedgenesanddrugsensitivityincervicalcancer
_version_	1718371956135297024

Comprehensive analysis of prognostic immune-related genes and drug sensitivity in cervical cancer

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